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At least 91 records · Page 5

System implications of large radiometric array antennas

Temperature sensitivity degradation due to antenna losses is recognized as a hindrance to extension of available remote-sensing radiometry techniques to larger systems for enhanced spatial resolution. The use of large antennas is also complicated by difficulties with bandwidth and integration time. Advantages of introducing active devices at the subarray level, with distributed Dicke switching or correlation detection, are examined, and their possible contribution to the design of effective imaging microwave radiometers for remote sensing of geophysical parameters (sea state, distribution of sea ice, cloud types and their distributions, soil moisture) is assessed.

Levis, C. A.↗

Phytoplankton in the Beaufort and Chukchi Seas: Distributions, Dynamics and Environmental Forcing

Time-series of remotely sensed distributions of phytoplankton, sea ice, surface temperature, albedo, and clouds were examined to evaluate the impact of the variability of environmental conditions and physical forcing on the phytoplankton distribution in the Beaufort and Chukchi Seas. Large-scale distributions of these parameters were studied for the first time using weekly and monthly composites from April 1998 through September 2002. The basic data set used in this study are phytoplankton pigment concentration derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), ice concentration obtained from the Special Sensor Microwave Imager (SSM/I) and surface temperature, cloud cover, and albedo derived from the Advanced Very High Resolution Radiometer (AVHRR). Seasonal variations of the sea ice cover was observed to be the dominant environmental factor as the ice edge blooms followed the retreating marginal ice zones northward. Blooms were most prominent in the southwestern Chukchi Sea, and were especially persistent immediately north of the Bering Strait in nutrient- rich Anadyr water and in some fronts. Chlorophyll concentrations are shown to increase from a nominal value during onset of melt in April to a maximum value in mid-spring or summer depending on location. Large interannual variability of ice cover and phytoplankton distributions was observed with the year 1998 being uniquely associated with an early season occurrence of a massive bloom. This is postulated to be caused in part by a rapid response of phytoplankton to an early retreat of the sea ice cover in the Beaufort Sea region. Correlation analyses showed relatively high negative correlation between chlorophyll and ice concentration with the correlation being highest in May, the correlation coefficient being -0.45. 1998 was also the warmest among the five years globally and the sea ice cover was least extensive in the Beaufort-Khukchi Sea region, partly because of the 1997-98 El Nino. Strong correlations were noted between ice extent and surface temperature, the correlation coefficient being highest at - 0.79 in April, during the onset of the bloom period

Wang, Jian↗

EPIC Cloud Observations with Oxygen Bands Over Snow, Ice and Sunglint Regions

Cloud detections over snow/ice surfaces and sunglint regions are challenging with passive remote sensing instrument due to lack of contract between cold/bright surfaces in the former and glint reflectance that could exceed that of cloudy sky in the latter. We developed novel cloud detection algorithms for these regions utilizing EPIC’s unique oxygen-bands. Over the snow and ice surfaces, a dynamic threshold scheme based on the ratios of two pairs of EPIC’s oxygen bands are developed to significantly improve the existing algorithm in these regions. Over the ocean, we improved the EPIC’s ocean cloud mask algorithm by implementing a dynamic reflectance threshold and supplemental A-band ratio test for cloud detection in the sun glint regions. The new ocean cloud mask algorithm improves the diurnal cycles of cloud fraction over ocean by reducing the artificial peak at local noon time in the glint center latitudes and reducing early morning and afternoon cloud fraction in most oceanic regions.

EPIC↗

Radiative Transfer and Satellite Remote Sensing of Cirrus Clouds Using FIRE-2-IFO Data

Under the support of the NASA grant, we have developed a new geometric-optics model (GOM2) for the calculation of the single-scattering and polarization properties for arbitrarily oriented hexagonal ice crystals. From comparisons with the results computed by the finite difference time domain (FDTD) method, we show that the novel geometric-optics can be applied to the computation of the extinction cross section and single-scattering albedo for ice crystals with size parameters along the minimum dimension as small as approximately 6. We demonstrate that the present model converges to the conventional ray tracing method for large size parameters and produces single-scattering results close to those computed by the FDTD method for size parameters along the minimum dimension smaller than approximately 20. We demonstrate that neither the conventional geometric optics method nor the Lorenz-Mie theory can be used to approximate the scattering, absorption, and polarization features for hexagonal ice crystals with size parameters from approximately 5 to 20. On the satellite remote sensing algorithm development and validation, we have developed a numerical scheme to identify multilayer cirrus cloud systems using AVHRR data. We have applied this scheme to the satellite data collected over the FIRE-2-IFO area during nine overpasses within seven observation dates. Determination of the threshold values used in the detection scheme are based on statistical analyses of these satellite data.

Source record↗

Ship-based Observations and Climate Model Simulations of Cloud Phase over the Southern Ocean

The Southern Ocean (SO) clouds exert a significant influence on the Earth’s radiation budget. Here we analyzed ship-based remote sensing observations of SO clouds over a five-month long DOE ARM Measurements of Aerosols, Radiation and Clouds over the Southern Oceans (MARCUS) field campaign to better understand cloud phase variability. We developed a method to classify eight categories of hydrometeors (ice, liquid, mixed phase, rain, drizzle, snow, aerosols, and clear sky) based on measurements of lidar, radar and radiosondes. Cloud thermodynamic phases (liquid, ice and mixed phase) at coarser scales were further derived to compare with the DOE Energy Exascale Earth System Model version 1 (E3SMv1) simulation and the Earth Model Column Collaboratory (EMC 2 ) instrument simulator. For a scale-aware comparison with climate model simulations, we found that spatially averaging the raw remote sensing data (e.g., backscatter, reflectivity) results in increased cloud cover and cloud liquid, whereas, directly averaging cloud phase from higher to lower resolution maintains clear air regions and is thus recommended for in-cloud frequency comparisons. For cloud thermodynamic phases in stratiform clouds, the E3SM underestimates cloud ice and overestimates cloud liquid at temperatures between -40 and 0°C. When latitudes increase, both observations and simulations show a transition of dominant phase from liquid to ice for cloud tops as well as for the entire cloud columns, but the model underestimation of ice phase is more severe at higher latitudes. Such model bias is unlikely caused by spatial scale differences or lack of heterogeneity in cloud vertical structure in the simulation.

54 ENVIRONMENTAL SCIENCES↗

Radiometric Calibration of A Non-Imaging Airborne Spectrometer To Measure the Greenland Ice Sheet Surface

Methods to radiometrically calibrate a non-imaging airborne visible-to-shortwave infrared (VSWIR) spectrometer to measure the Greenland ice sheet surface are presented. Airborne VSWIR measurement performance for bright Greenland ice and dark bare rock/soil targets is compared against the MODerate resolution atmospheric TRANsmission (MODTRAN ® ) radiative transfer code (version 6.0), and a coincident Landsat 8 Operational Land Imager (OLI) acquisition on 29 July 2015 during an in-flight radiometric calibration experiment. Airborne remote sensing flights were carried out in northwestern Greenland in preparation for the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) laser altimeter mission. A total of nine science flights were conducted over the Greenland ice sheet, sea ice, and open-ocean water. The campaign's primary purpose was to correlate green laser pulse penetration into snow and ice with spectroscopic-derived surface properties. An experimental airborne instrument configuration that included a nadir-viewing (looking downward at the surface) non-imaging Analytical Spectral Devices (ASD) Inc. spectrometer that measured upwelling VSWIR (0.35 to 2.5 µm) spectral radiance (Wm −2 sr −1 µm −1 ) in the two-color Slope Imaging Multi-polarization Photon-Counting Lidar's (SIMPL) ground instantaneous field of view, and a zenith-viewing (looking upward at the sky) ASD spectrometer that measured VSWIR spectral irradiance (W m −2 nm −1 ) was flown. National Institute of Standards and Technology (NIST) traceable radiometric calibration procedures for laboratory, in-flight, and field environments are described in detail to achieve a targeted VSWIR measurement requirement of within 5 % to support calibration/validation efforts and remote sensing algorithm development. Our MODTRAN predictions for the 29 July flight line over dark and bright targets indicate that the airborne nadir-viewing spectrometer spectral radiance measurement uncertainty was between 0.6 % and 4.7 % for VSWIR wavelengths (0.4 to 2.0 µm) with atmospheric transmittance greater than 80 %. MODTRAN predictions for Landsat 8 OLI relative spectral response functions suggest that OLI is measuring 6 % to 16 % more top-of-atmosphere (TOA) spectral radiance from the Greenland ice sheet surface than was predicted using apparent reflectance spectra from the nadir-viewing spectrometer. While more investigation is required to convert airborne VSWIR spectral radiance into atmospherically corrected airborne surface reflectance, it is expected that airborne science flight data products will contribute to spectroscopic determination of Greenland ice sheet surface optical properties to improve understanding of their potential influence on ICESat-2 measurements.

Christopher J. Crawford↗

A New Way to Measure Cirrus Ice Water Content by Using Ice Raman Scatter with Raman Lidar

High and cold cirrus clouds mainly contain irregular ice crystals, such as, columns, hexagonal plates, bullet rosettes, and dendrites, and have different impacts on the climate system than low-level clouds, such as stratus, stratocumulus, and cumulus. The radiative effects of cirrus clouds on the current and future climate depend strongly on cirrus cloud microphysical properties including ice water content (IWC) and ice crystal sizes, which are mostly an unknown aspect of cinus clouds. Because of the natural complexity of cirrus clouds and their high locations, it is a challenging task to get them accurately by both remote sensing and in situ sampling. This study presents a new method to remotely sense cirrus microphysical properties by using ice Raman scatter with a Raman lidar. The intensity of Raman scattering is fundamentally proportional to the number of molecules involved. Therefore, ice Raman scattering signal provides a more direct way to measure IWC than other remote sensing methods. Case studies show that this method has the potential to provide essential information of cirrus microphysical properties to study cloud physical processes in cirrus clouds.

Wang, Zhien↗

Applications of radar imagery to arctic and subarctic problems

Radar imagery provides year around data acquisition of areas in the Arctic and the Subarctic. The foremost factor influencing the choice of radar imagery as the major data source was the demand for neotric data. The weather is so adverse in parts of Alaska that radar imagery was the only remote sensing technique which could meet the demand. The major map products derived from radar imagery are landform maps and lineament maps. These maps are used to make environmental assessments of areas and to reconstruct the geomorphic history of certain regions or features. Since radar imagery provides information about geologic structure and geomorphic features, it can be used to determine the relationship which exists between geologic structure and geomorphology. Important geologic information related to surface roughness can be obtained through a dry snow cover. Radar imagery is the only remote sensing technique which can provide information needed about sea ice through a cloud cover and dry snow, during strong wind conditions, and throughout the Arctic night.

Cannon, P. J.↗

The Area Coverage of Geophysical Fields as a Function of Sensor Field-of View

In many remote sensing studies of geophysical fields such as clouds, land cover, or sea ice characteristics, the fractional area coverage of the field in an image is estimated as the proportion of pixels that have the characteristic of interest (i.e., are part of the field) as determined by some thresholding operation. The effect of sensor field-of-view on this estimate is examined by modeling the unknown distribution of subpixel area fraction with the beta distribution, whose two parameters depend upon the true fractional area coverage, the pixel size, and the spatial structure of the geophysical field. Since it is often not possible to relate digital number, reflectance, or temperature to subpixel area fraction, the statistical models described are used to determine the effect of pixel size and thresholding operations on the estimate of area fraction for hypothetical geophysical fields. Examples are given for simulated cumuliform clouds and linear openings in sea ice, whose spatial structures are described by an exponential autocovariance function. It is shown that the rate and direction of change in total area fraction with changing pixel size depends on the true area fraction, the spatial structure, and the thresholding operation used.

Key, Jeffrey R.↗

Passive Microwave Remote Sensing of Falling Snow and Associated GPM Field Campaigns

Retrievals of falling snow from space represent one of the next important challenges for the atmospheric, hydrological, and energy budget scientific communities. Historically, retrievals of falling snow have been difficult due to the relative insensitivity of satellite rain-based channels as used in the past. We emphasize the use of high frequency passive microwave channels (85-200 GHz) since these are more sensitive to the ice in clouds and have been used to estimate falling snow from space. While satellite-based remote sensing provides global coverage of falling snow events and the science is relatively new, retrievals are still undergoing development with challenges remaining. There are several current satellite sensors, though not specifically designed for estimating falling snow, are capable of measuring snow from space. These include NOAA's AMSU-B, the MHS sensors, and CloudSat radar. They use high frequency (greater than 85 GHz) passive and active microwave and millimeter-wave channels that are sensitive to the scattering from ice and snow particles in the atmosphere. Sensors with water vapor channels near 183 GHz center line provide opaqueness to the Earth's surface features that can contaminate the falling snow signatures, especially over snow covered surface. In addition, the Global Precipitation Measurement (GPM) mission scheduled for launch in 2013 is specifically designed to measure both liquid rain and frozen snow precipitation. Since falling snow from space is the next precipitation measurement challenge from space, information must be determined in order to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, snow event system characteristics, and surface types. For example, can a lake effect snow system with low cloud tops having an ice water content (IWC) at the surface of 1.0 gram per cubic meter be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. In this work, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The results rely on simulated Weather Research Forecasting (WRF) simulations of falling snow cases [9] since simulations provide all the information to determine the measurements from space and the ground truth. This analysis relies on data from the Canadian CloudSat/CALIPSO Validation Program (C3VP) field campaign held from October 31, 2006 through March 1, 2007. In January 2012 GPM will return to the C3VP area for the GPM Cold Precipitation Experiment (GCPEx). This presentation will describe the thresholds-of-detection procedure and results, as well as the field campaign details.

Skofronick-Jackson, Gail↗

Diagnosing Aircraft Icing Potential from Satellite Cloud Retrievals

The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This paper describes new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content (IWC and LWC) profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS and ground-based icing remote sensing datasets, the satellite icing detection and intensity accuracies are approximately 90% and 70%, respectively, and found to be similar for both low level and deep ice over water cloud systems. The satellite-derived icing boundaries capture the reported altitudes over 90% of the time. Satellite analyses corresponding to the time and location of several recent aviation accidents and with icing PIREPS are also presented that reveal skill in identifying severe icing conditions. These results demonstrate the utility of satellite cloud retrievals for quantitatively diagnosing the potential for icing conditions on temporal and spatial scales that should be useful to the aviation community. Plans are being developed to deliver these new satellite products to the GOES-R Proving Ground in the near future so that they can be evaluated in operational applications.

Smith, William L., Jr.↗

The Atmospheric Channels of GLAS: Near Real-Time Global Lidar Remote Sensing of Clouds and Aerosols from Space

The Geoscience Laser Altimeter System (GLAS) will be placed into orbit in 2001 aboard the Ice, Cloud and Land Elevation Satellite (ICESat). From its nearly polar orbit (94 degree inclination), GLAS will provide continuous global measurements of the vertical distribution of clouds and aerosols while simultaneously providing high accuracy topographic profiling of surface features. During the mission, which is slated to last 3 to 5 years, the data collected by GLAS will be in near-real time to produce level 1 and 2 data products at the NASA GLAS Science Computing Facility (SCF) at Goddard Space Flight Center in Greenbelt, Maryland. The atmospheric products include cloud and aerosol layer heights, planetary boundary layer depth, polar stratospheric clouds and thin cloud and aerosol optical depth. These products will be made available to the science community within days of their creation. The processing algorithms must be robust, adaptive, efficient, and clever enough to run autonomously for the widely varying atmospheric conditions that will be encountered. This paper presents an overview of the GLAS atmospheric data products and briefly discusses the design of the processing algorithms.

Palm, Stephen P.↗

Validation of the Cloud_CCI (Cloud Climate Change Initiative) cloud products in the Arctic

The role of clouds in the Arctic radiation budget is not well understood. Ground-based and airborne measurements provide valuable data to test and improve our understanding. However, the ground-based measurements are intrinsically sparse, and the airborne observations are snapshots in time and space. Passive remote sensing measurements from satellite sensors offer high spatial coverage and an evolving time series, having lengths potentially of decades. However, detecting clouds by passive satellite remote sensing sensors is challenging over the Arctic because of the brightness of snow and ice in the ultraviolet and visible spectral regions and because of the small brightness temperature contrast to the surface. Consequently, the quality of the resulting cloud data products needs to be assessed quantitatively. In this study, we validate the cloud data products retrieved from the Advanced Very High Resolution Radiometer (AVHRR) post meridiem (PM) data from the polar-orbiting NOAA-19 satellite and compare them with those derived from the ground-based instruments during the sunlit months. The AVHRR cloud data products by the European Space Agency (ESA) Cloud Climate Change Initiative (Cloud_CCI) project uses the observations in the visible and IR bands to determine cloud properties. The ground-based measurements from four high-latitude sites have been selected for this investigation: Hyytiälä (61.84°N, 24.29°E), North Slope of Alaska (NSA; 71.32°N, 156.61°W), Ny-Ålesund (Ny-Å; 78.92°N, 11.93°E), and Summit (72.59°N, 38.42°W). The liquid water path (LWP) ground-based data are retrieved from microwave radiometers, while the cloud top height (CTH) has been determined from the integrated lidar–radar measurements. The quality of the satellite products, cloud mask and cloud optical depth (COD), has been assessed using data from NSA, whereas LWP and CTH have been investigated over Hyytiälä, NSA, Ny-Å, and Summit.

54 ENVIRONMENTAL SCIENCES↗

Microphysical properties of the November 26 cirrus cloud retrieved by Doppler radar/IR radiometer technique

Gaining information about cirrus cloud microphysics requires development of remote sensing techniques. In an earlier paper. Matrosov et al. (1992) proposed a method to estimate ice water path (IWP) (i.e., vertically integrated ice mass content IMC) and characteristic particle size averaged through the cloud from combined groundbased measurements of radar reflectivities and IR brightness temperatures of the downwelling thermal radiation in the transparency region of 10-12 mu m. For some applications, the vertically averaged characteristic particle sizes and IWP could be the appropriate information to use. However, vertical profiles of cloud microphysical parameters can provide a better understanding of cloud structure and development. Here we describe a further development of the previous method by Matrosov et al. (1992) for retrieving vertical profiles of cirrus particle sizes and IMC rather than their vertically averaged values. In addition to measurements of radar reflectivities, the measurements of Doppler velocities are used in the new method. This provides us with two vertical profiles of measurements to infer two vertical profiles of unknowns, i.e., particle characteristic sizes and IMC. Simultaneous measurements of the IR brightness temperatures are still needed to resolve an ambiguity in particle size-fall velocity relationships.

Matrosov, Sergey Y.↗

Remote sensing over oceans of optically thin cirrus and its significance

The extinction characteristics of thin ice-crystal clouds over the oceanic convective rain belts in the tropics and midlatitudes, obtained from the infrared interferometer spectrometer flown on Nimbus 4 satellite in 1970 are examined. It is observed that the optical depth of these clouds in the RF window region is less than 3 and their spectral features are consistent with the cloud particle size of about 10 micron. These optically-thin ice-crystal clouds are extensions of the anvil clouds generated by deep convective systems. The existence of such clouds extending from the upper troposphere into the lower stratosphere in the polar regions during winter and early spring is indicated, and the result of a theoretical simulation are analyzed.

Cuddapah, Prabhakara↗

Global Retrieval of Cloud Particle Size and Optical Thickness Using ISCCP Data

The primary thrust of this investigation is to develop an algorithm to retrieve cloud particle sizes using ISCCP data. The research under this grant has been successful in obtaining initial results of global distribution of ice-particle sizes. Further research about possible problems caused by nonsphericity of ice particle sizes is currently underway. An algorithm of retrieving ice-cloud particle sizes using ISCCP CX data has been developed. The first survey of ice-particle size in a near-global scale has been completed. Comparison with in situ measurements of ice crystal sizes during FIRE I shows good agreement. The initial results show that the global mean size of ice crystals (De) is about 60 micron. This result is consistent with the range of in situ measurements all over the world if definitions of effective particle size are unified (see next section). The survey also shows that there is no distinct difference of ice-particle sizes between continental and maritime ice-clouds. There are many different definitions of effective particle size used in ice-cloud research. Simple comparisons between values of in situ measurement and satellite remote sensing are misleading and may lead to incorrect conclusions. We reviewed different definitions of effective particle sizes used in the literature and compared their relative magnitudes.

Welch, Ronald M.↗

CoSSIR: A New Instrument for Exploring the Utility of Submillimeter-wave Radiometry for Earth Observation

The Conical Scanning Submillimeter-wave Imaging Radiometer (CoSSIR) has been developed to study the application of submillimeter-wave radiometry for remote sensing of cirrus clouds and humidity sounding. Measurements of the global distribution of ice cloud mass and particle size are important for understanding the Earth s energy budget and for evaluating global climate models. The spatial variability and the wide variety of cloud particle shapes and sizes make ice clouds particularly difficult to measure. Ice clouds are essentially undetectable at microwave frequencies due to the low dielectric of ice and small size of the particles relative to wavelength. However, submillimeter wavelengths demonstrate significant response to the presence of ice clouds thus this frequency regime is applicable to measuring ice clouds. Another potentially viable application for submillimeter-wave radiometry is humidity and temperature sounding. The principle of sounding at submillimeter wavelengths is similar to that at microwavelengths. Submillimeter-wave radiometry has the advantage of achieving finer spatial resolution using a smaller antenna aperture which is an important consideration for spaceborne observatories. Submillimeter-wave radiometry also offers the potential of sounding over land and as a surrogate measurement for precipitation. CoSSIR is a new instrument to explore these applications. The CoSSIR is designed to fly aboard the ER-2 aircraft and its modest size (approximately 100 kg) permits it to be configured for other aircraft. A dual-axes gimbals mechanism provides conical, across-track, and along-track scanning capability. In its present configuration CoSSIR has fifteen channels between 183 GHz and 640 GHz. Three channels are centered about the 183 GHz water vapor absorption line, four channels are centered about the 380 GHz water vapor absorption line, and three dual-polarized channels are centered about the 487 GHz oxygen absorption line. Two channels are located in atmospheric windows at 220 GHz and 640 GHz. All channels are single-linear polarized with the exception of those near 487 GHz. Calibration is achieved by periodically observing two blackbody radiators; one blackbody is heated to approximately 325 K and the other is approximately 250 K during flight. Details of the instrument design as well as measurements from the Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment will be presented.

Racette, P. E.↗